«上一篇/Previous Article|本期目录/Table of Contents|下一篇/Next Article»

《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:

期数:

2013年04期

页码:

154-158

栏目:

安全与防范

出版日期:

1900-01-01

文章信息/Info

Title:

An Attribute Value Reduction Algorithm of Expert System Knowledge Acquisition

文章编号:

1673-629X（2013）04-0154-05

作者:

彭霞; 朱萍; 任永昌

渤海大学 信息科学与技术学院

Author(s):

FENG Xia; ZHU Ping; REN Yong-chang

关键词:

专家系统; 知识获取; 属性值约简算法; 粗糙集理论

Keywords:

expert system; knowledge acquisition; attribute value reduction algorithms; rough sets theory

文献标志码:

A

摘要:

知识获取是构造专家系统的“瓶颈”,提供准确的推理知识是进行科学决策的关键.文中运用粗糙集理论,研究对决策表中每条记录的冗余条件属性值进行筛选并删除的属性值约简算法.首先研究属性值约简的理论基础,包括知识表示和知识约简与核两个方面;其次研究知识获取方式与知识获取过程;然后研究属性值约简算法,通过两个定义描述约简算法的基础上,给出了约简算法的5个步骤;最后以城市物流中心选址为例,运用属性值约简算法及其步骤,对决策表属性值进行约简.结果表明,属性值约简实现了决策表的最简化,突出了关键属性及其关键属性值对决策的影响

Abstract:

To construct an expert system,knowledge acquisition is the"bottleneck" problem,and the key to scientific decision-making is accurate inference knowledge. In this paper,it will use rough sets theory to attribute value reduction algorithms that filter and remove the redundant condition attribute value of decision-making table’s each record. First,research the theoretical basis of attribute value reduc-tion,including knowledge representation and knowledge reduction and core both. Then,research knowledge acquisition ways and knowl-edge acquisition processes. Third,research the attribute value reduction algorithms,through the description of two definitions the reduction algorithms is given the 5 steps. Finally,take the city logistics center location as example,use attribute value reduction algorithms and its steps for the value of decision table attribute reduction. The results show that attribute value reduction achieves the most streamlined deci-sion-making table,highlighting the key attributes and key decision-making of property value

常用功能

更新日期/Last Update: 1900-01-01